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Record W2973058490 · doi:10.1177/1077801219870608

Online Interpersonal Victimization as a Mechanism of Social Control of Women: An Empirical Examination

2019· article· en· W2973058490 on OpenAlexaffabout
Cassandra Hill, Holly Johnson

Bibliographic record

VenueViolence Against Women · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicStalking, Cyberstalking, and Harassment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInterpersonal communicationPoison controlHuman factors and ergonomicsSuicide preventionSocial controlInjury preventionPsychologySpace (punctuation)Computer securitySocial psychologyControl (management)Occupational safety and healthInterpersonal relationshipInterpersonal violenceDevelopmental psychologySociologyMedical emergencyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Cyber space is an ever-expanding mode of perpetrating sexualized violence toward women. This article empirically examines the applicability of Susan Brownmiller's adaptation of the theory of social control to online interpersonal victimization (OIV) against women. Multiple regression analysis identified predictors of behaviors indicative of social control among a Canadian sample. Findings suggest that the theory of social control, which has been applied to violence against women in physical space, is applicable to OIV. This study also provides insights into the separate and compound effects of physical space and cyber space victimizations on women and identifies implications for improving methods and building theories for addressing violence against women in cyber space.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.304
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2019
Admission routes2
Has abstractyes

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